The OAI Osteoarthritis (OA) is the most common cause of arthritis. Approximately 21 million Americans have physician diagnosed OA and many more have undiagnosed disease. Knee OA is responsible for as much chronic disability in the elderly as cardiovascular disease and more disability than any other medical condition. Identifying individuals at risk for knee OA is critical for reducing the burden of this disease and there are increasing data suggesting that genetic factors play an important role in determining population variability in a variety of OA phenotypes. Thus, the goal of this project is to identify genetic alterations that increase susceptibility to knee OA among middle-aged and older men and women by individually genotyping all 4800 participants in the Osteoarthritis Initiative (OAI). The OAI was designed to determine the validity of imaging, biochemical, and genetic markers as surrogate endpoints for OA disease development and progression (worsening of established disease). With the spectrum of carefully characterized phenotypes within the OAI, the OAI affords the opportunity to systematically examine the genetic underpinnings of a variety of OA structural, clinical and functional phenotypes and traits. By employing a genome-wide association study rather than a candidate gene approach, the agnostic selection of genes offers opportunities to identify associations without preconceived hypotheses that could offer new insights into the pathophysiology of OA. As a demonstration of the power of this new resource to explore genetic factors contributing to risk for OA, we will perform analyses of the genetic associations of radiographic knee OA. An important feature of our proposal is the inclusion of an 'in silico'replication in the Johnston County Osteoarthritis Project followed by genotyping of the SNPs most strongly associated with radiographic knee OA within the NIH-funded Multicenter Osteoarthritis Study (MOST), an independent cohort with a similar study design and standardized clinical phenotype definitions allowing for assessment of validity and comparability. Finally, we will take advantage of a second GWAS conducted as part of Arthritis Research Campaign Osteoarthitic Genetics to determine whether the SNPs reliably associated with radiographic OA contribute to risk for knee replacement. The results from this project should provide valuable insights into disease pathways and mechanisms, thus helping in the identification of novel targets for screening, prevention, and treatment of OA. In addition, by performing this GWAS within the Osteoarthritis Initiative, a public use dataset, this study becomes a national resource to facilitate investigators from diverse scientific fields to utilize the GWAS to begin to explore putative causal genetic variants for a wide range of musculoskeletal phenotypes captured in the OAI. The inclusion of the GWAS data to the OAI dataset will lend incremental value to the OAI as a scientific resource for years to come. This project is submitted in response to the American Recovery and Reinvestment Act (ARRA) Research and Research Infrastructure 'Grand Opportunities'RC2 program (RFA-OD-09-004). The proposed work is in line with the goals of the ARRA, accelerating the tempo of science and leading to significant job retention and creation.